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  • Goodness of fit - structural equation modeling (GSEM)

    Greetings,

    Using Stata 13:

    When using the GSEM (generalized structural equation model) it would appear the options to test for goodness of fit are grayed out. How do I test my model(s) goodness of fit?

    Is having negative ‘B’s’ appropriate?
    I’m also estimating using ‘clustered robust’, would matrices of residuals be best to assess goodness of fit?

    I am new to structural equation modeling.

    Thanks and yours sincerely,
    Gwinyai

  • #2
    -help sem estat gof- says "estat gof is for use after sem but not gsem." I don't see why negative coefficients would be inappropriate.
    -------------------------------------------
    Richard Williams, Notre Dame Dept of Sociology
    StataNow Version: 19.5 MP (2 processor)

    EMAIL: [email protected]
    WWW: https://www3.nd.edu/~rwilliam

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    • #3
      Many thanks Richard. Does this mean when using GSEM one does not test goodness of fit? A perhaps elementary question - what's the major difference between SEM and GSEM?

      Comment


      • #4
        http://www.stata.com/stata13/generalized-sem/
        -------------------------------------------
        Richard Williams, Notre Dame Dept of Sociology
        StataNow Version: 19.5 MP (2 processor)

        EMAIL: [email protected]
        WWW: https://www3.nd.edu/~rwilliam

        Comment


        • #5
          If sem can meet your needs, use it. http://www.stata.com/stata12/structu...tion-modeling/
          -------------------------------------------
          Richard Williams, Notre Dame Dept of Sociology
          StataNow Version: 19.5 MP (2 processor)

          EMAIL: [email protected]
          WWW: https://www3.nd.edu/~rwilliam

          Comment


          • #6
            Thanks.

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            • #7
              Sometimes a GSEM will allow a negative variance for some variance parameters; compared to Lisrel and Mplus, it is much more forgiving of what would otherwise be "Heywood cases." Which is good, because the imposition of a positive variance is a bit arbitrary when the variance itself is not directly computed using some sort of sum-squared formula. But it plays havoc with goodness-of-fit indices, which are predicated on positive variances. Negative variances are a non-issue when the software won't allow you to have them. But GSEM lets you make up your mind whether such anomalies are acceptable, and thus will not automatically dish out GFI type numbers.

              Check out SEMnet, devoted to SEM, and you may get a better and more complete answer, but I hope this helps a bit as to why GSEM won't do GFIs, indirect effects, and some other things we take for granted.
              Last edited by ben earnhart; 25 Jun 2014, 21:27. Reason: clarification/extension.

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              • #8
                ps: http://www2.gsu.edu/~mkteer/semnet.html#Joining for taking your question to SEMNET. Yes, the Stata folks cross-breed with them to a large degree, but taking advantage of a SEM-specific community could help get you a good answer, and possible alternatives using Lisrel or Mplus.

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                • #9
                  Thanks Ben.

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                  • #10
                    I have another question related to gof
                    Is it possible to assess model fit when using vce(cluster clustervar) in sem?
                    Found this thread http://www.stata.com/statalist/archi.../msg00800.html but considering it's couple years old, and sem in state has improved quite a bit since then, I was wondering whether this is still the case.

                    Thanks

                    Comment


                    • #11
                      You may have look to the following paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087284/

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